Post-stroke respiratory complications using machine learning with voice features from mobile devices

Abnormal voice may identify those at risk of post-stroke aspiration. This study was aimed to determine whether machine learning algorithms with voice recorded via a mobile device can accurately classify those with dysphagia at risk of tube feeding and post-stroke aspiration pneumonia and be used as...

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Detalles Bibliográficos
Autores principales: Park, Hae-Yeon, Park, DoGyeom, Kang, Hye Seon, Kim, HyunBum, Lee, Seungchul, Im, Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537337/
https://www.ncbi.nlm.nih.gov/pubmed/36202829
http://dx.doi.org/10.1038/s41598-022-20348-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537337/
https://www.ncbi.nlm.nih.gov/pubmed/36202829
http://dx.doi.org/10.1038/s41598-022-20348-8

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